Utilizing machine learning models and captured video of a vehicle to determine a valuation for the vehicle

Abstract

A valuation platform may receive, from a user device, video data associated with a vehicle, and may receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle. The valuation platform may receive, from the user device, feature data associated with the vehicle, and may process the video data, the vehicle history report, and the feature data, with a machine learning model, to determine one or more values for the vehicle. The valuation platform may determine a valuation for the vehicle based on the determined one or more values for the vehicle. The valuation platform may create a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the determined one or more values for the vehicle, and the valuation for the vehicle, and may perform one or more actions based on the vehicle profile.

What is claimed is: 
     
       1. A method, comprising:
 receiving, by a device and from a user device, video data identifying one or more conditions of a vehicle,
 wherein receiving the video data is based on providing instructions via the user device to capture a series of vehicle features in operation, including:
 a first video of activating and deactivating a first vehicle feature, and 
 a second video of a second vehicle feature in operation; 
 
 
 receiving, by the device, a vehicle history report of the vehicle based on a vehicle identification number of the vehicle; 
 receiving, by the device and from the user device, feature data associated with the vehicle; 
 processing, by the device, the video data, the vehicle history report, and the feature data, with a machine learning model, to determine one or more values for the vehicle,
 wherein the machine learning model is trained based on historical video data, historical vehicle history reports, and historical feature data, and 
 wherein the machine learning model is trained based on:
 performing an artificial neural network processing technique to perform pattern recognition with regard to patterns of the historical video data, the historical vehicle history reports, the historical feature data, and historical values, 
 
 wherein the machine learning model processes the first video of activating and deactivating the first vehicle feature and the second video of the second vehicle feature in operation to determine the one or more values for the vehicle; 
 
 determining, by the device and using a model, a valuation for the vehicle based on the one or more values for the vehicle,
 wherein the model is configured to generate the valuation based on the one or more values for the vehicle and a historical range of values associated with historical sales information; and 
 
 creating, by the device, a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the one or more values for the vehicle, and the valuation for the vehicle. 
 
     
     
       2. The method of  claim 1 , wherein the video data additionally comprises an image or a video of the vehicle identification number. 
     
     
       3. The method of  claim 1 , further comprising:
 performing optical character recognition on the video data to identify the vehicle identification number. 
 
     
     
       4. The method of  claim 1 , wherein the feature data includes one or more of:
 data identifying working features of the vehicle, 
 audio of an operating engine of the vehicle, or 
 data identifying tire treadwear of the vehicle. 
 
     
     
       5. The method of  claim 1 , wherein processing the video data, the vehicle history report, and the feature data, with the machine learning model comprises:
 processing the video data, the vehicle history report, and the feature data, with the machine learning model to create a range of values for the vehicle based on an exterior condition of the vehicle, an interior condition of the vehicle and the feature data. 
 
     
     
       6. The method of  claim 1 , wherein determining the valuation for the vehicle comprises:
 determining the valuation based on an average of the one or more values. 
 
     
     
       7. The method of  claim 1 , wherein the vehicle profile identifies one or more of:
 the video data, 
 the vehicle history report, 
 the feature data, 
 the one or more values, or 
 the valuation. 
 
     
     
       8. A device, comprising:
 one or more memories; and 
 one or more processors, coupled to the one or more memories, configured to:
 receive, from a user device, video data identifying one or more conditions of a vehicle,
 wherein the video data is received based on providing instructions via the user device to capture a series of vehicle features in operation, including:
 a first video of activating and deactivating a first vehicle feature, and 
 a second video of a second vehicle feature in operation; 
 
 
 receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle; 
 receive, from the user device, feature data associated with the vehicle; 
 process the video data, the vehicle history report, and the feature data, with one or more machine learning models, to determine one or more values for the vehicle,
 wherein the one or more machine learning models are trained based on historical video data, historical vehicle history reports, or historical feature data, and 
 wherein the one or more machine learning models are trained based on:
 performing an artificial neural network processing technique to perform pattern recognition with regard to patterns of the historical video data, the historical vehicle history reports, the historical feature data, and historical values; 
 
 
 determine, using a model, a valuation for the vehicle based on the one or more values for the vehicle,
 wherein the model is configured to generate the valuation based on the one or more values for the vehicle and a historical range of values associated with historical sales information; and 
 
 create a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the one or more values for the vehicle, and the valuation for the vehicle. 
 
 
     
     
       9. The device of  claim 8 , wherein the video data additionally comprises an image or a video of the vehicle identification number; and
 wherein the one or more processors are further configured to:
 perform an optical character recognition technique on the video data to identify the vehicle identification number. 
 
 
     
     
       10. The device of  claim 8 , wherein the feature data includes one or more of:
 audio of an operating engine of the vehicle, or 
 data identifying tire treadwear of the vehicle. 
 
     
     
       11. The device of  claim 8 , wherein the one or more processors, to process the video data, the vehicle history report, and the feature data, with the one or more machine learning models, are configured to:
 process the video data, with a first machine learning model, of the one or more machine learning models, to determine a condition of the vehicle. 
 
     
     
       12. The device of  claim 11 , wherein the one or more processors, to process the video data, the vehicle history report, and the feature data, with the one or more machine learning models, are configured to:
 process the feature data, with a second machine learning model, of the one or more machine learning models, to determine working features of the vehicle. 
 
     
     
       13. The device of  claim 12 , wherein the one or more processors, to process the video data, the vehicle history report, and the feature data, with the one or more machine learning models, are configured to:
 determine the one or more values based on the condition of the vehicle, and the working features. 
 
     
     
       14. The device of  claim 8 , wherein the vehicle profile identifies information, images, and audio based on one or more of:
 the video data, 
 the vehicle history report, 
 the feature data, 
 the one or more values, or 
 the valuation. 
 
     
     
       15. A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:
 one or more instructions that, when executed by one or more processors of a device, cause the device to:
 receive, from a user device, video data identifying one or more conditions of a vehicle,
 wherein the video data is received based on providing instructions via the user device to capture a series of vehicle features in operation, including:
 a first video of activating and deactivating a first vehicle feature, and 
 a second video of a second vehicle feature in operation; 
 
 
 receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle; 
 receive, from the user device, feature data associated with the vehicle; 
 process the video data, the vehicle history report, and the feature data, with a machine learning model, to determine a range of values for the vehicle,
 wherein the machine learning model is trained based on historical video data, historical vehicle history reports, and historical feature data, and 
 wherein the machine learning model is trained based on:
 performing an artificial neural network processing technique to perform pattern recognition with regard to patterns of the historical video data, the historical vehicle history reports, the historical feature data, and historical values; 
 
 
 determine, using a model, a valuation for the vehicle based on the range of values for the vehicle,
 wherein the model is configured to generate the valuation based on range of values for the vehicle and a historical range of values associated with historical sales information; and 
 
 create a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the range of values for the vehicle, and the valuation for the vehicle. 
 
 
     
     
       16. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 identify, based on the vehicle profile, one or more of:
 offers for the vehicle, 
 trade-in reductions for the vehicle, 
 a new vehicle for which to trade in the vehicle, or 
 financing for the new vehicle. 
 
 
     
     
       17. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 provide the valuation for the vehicle to a plurality of entities that provide offers for the vehicle based on the valuation for the vehicle, 
 provide the valuation for the vehicle to a consumer lending platform that calculates terms for a new vehicle based on the valuation for the vehicle, or 
 provide the valuation for the vehicle to a plurality of consumers that provide offers for the vehicle based on the valuation for the vehicle. 
 
     
     
       18. The non-transitory computer-readable medium of  claim 15 , wherein the historical feature data identifies one or more of:
 historical data identifying working features of a plurality of historical vehicles, 
 historical data identifying audio of a plurality of operating engines, or 
 historical data identifying tire treadwear of a plurality of historical vehicles. 
 
     
     
       19. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 provide, to the user device, information identifying the one or more offers for the vehicle; 
 receive, from the user device, a selection of a particular offer from the one or more offers,
 wherein the particular offer is associated with a particular dealership; and 
 
 connect, based on the selection, the user device with a user device associated with the particular dealership. 
 
     
     
       20. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 receive information identifying one or more terms for one or more new vehicles from lenders based on the valuation; 
 provide, to the user device, the information identifying the one or more terms; 
 receive, from the user device, information identifying a selection of a new vehicle of the one or more new vehicles,
 wherein the new vehicle is associated with a particular consumer lending platform; and 
 
 
       connect, based on the selection, the user device with the particular consumer lending platform.